cubical: Calculate Persistent Homology using a Cubical Complex

In ripserr: Calculate Persistent Homology with Ripser-Based Engines

Description

Calculates the persistent homology of a 2- to 4-dimensional numeric array using a Cubical complex. This function is an R wrapper for Takeki Sudo and Kazushi Ahara's Cubical Ripser C++ library. For more information on the C++ library, see https://github.com/CubicalRipser.

Usage

cubical(
  dataset,
  threshold = 9999,
  method = 0,
  standardize = FALSE,
  return_format = "df"
)

Arguments

dataset	numeric array containing pixel/voxel data
threshold	maximum diameter for computation of Cubical complex
method	defaults to 0 for link join; alternatively, can be 1 for compute pairs. See original Cubical Ripser code at GitHub user CubicalRipser for details.
standardize	boolean determining whether point cloud size should be standardized
return_format	defaults to "df", returning a data frame; if mat, returns a numeric matrix

Value

3-column matrix with each row representing a TDA feature

Examples

# 2-dim example
dataset <- rnorm(10 ^ 2)
dim(dataset) <- rep(10, 2)
cubical_hom2 <- cubical(dataset)

# 3-dim example
dataset <- rnorm(8 ^ 3)
dim(dataset) <- rep(8, 3)
cubical_hom3 <- cubical(dataset)

# 4-dim example
dataset <- rnorm(5 ^ 4)
dim(dataset) <- rep(5, 4)
cubical_hom4 <- cubical(dataset)

ripserr documentation built on Oct. 23, 2020, 7:25 p.m.